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Novel approach towards musculoskeletal phenotypes

PainSci » bibliography » Meisingset et al 2020
updated

One page on PainSci cites Meisingset 2020: Diagnosis or the patient? What matters more for prognosis

PainSci commentary on Meisingset 2020: ?This page is one of thousands in the PainScience.com bibliography. It is not a general article: it is focused on a single scientific paper, and it may provide only just enough context for the summary to make sense. Links to other papers and more general information are provided wherever possible.

This trial applied a fancy "sorting hat" to group people with musculoskeletal pain: more than 400 Norwegians with undiagnosed neck, shoulder, low back pain, complex body pain. They were classified according to share traits from “across the biopsychosocial domains” — anything that has ever been considered a likely factor in the prognosis of body pain, things like pain intensity, activity level, sleep problems, mental distress, and many more. Five groups were identified, and people with the same condition could were often in different groups.

For an example of how this classification system is useful, see Aasdahl et al, which conclude that prognosis is predicted much better by these groupings than by condition.

~ Paul Ingraham

original abstract Abstracts here may not perfectly match originals, for a variety of technical and practical reasons. Some abstacts are truncated for my purposes here, if they are particularly long-winded and unhelpful. I occasionally add clarifying notes. And I make some minor corrections.

BACKGROUND: The multidimensional array of clinical features and prognostic factors makes it difficult to optimize management within the heterogeneity of patients with common musculoskeletal pain. This study aimed to identify phenotypes across prognostic factors and musculoskeletal complaints. Concurrent and external validity were assessed against an established instrument and a new sample, respectively, and treatment outcome was described.

METHODS: We conducted a longitudinal observational study of 435 patients (aged 18-67 years) seeking treatment for nonspecific complaints in the neck, shoulder, low back or multisite/complex pain in primary health care physiotherapy in Norway. Latent class analysis was used to identify phenotypes based on 11 common prognostic factors within four biopsychosocial domains; pain, beliefs and thoughts, psychological and activity and lifestyle.

RESULTS: Five distinct phenotypes were identified. Phenotype 1 (n = 77, 17.7%) and 2 (n = 142, 32.6%) were characterized by the lowest scores across all biopsychosocial domains. Phenotype 2 showed somewhat higher levels of symptoms across the biopsychosocial domains. Phenotype 3 (n = 89, 20.5%) and 4 (n = 78, 17.9%) were more affected across all domains, but phenotype 3 and 4 had opposite patterns in the psychological and pain domains. Phenotype 5 (n = 49, 11.3%) were characterized by worse symptoms across all domains, indicating a complex phenotype. The identified phenotypes had good external and concurrent validity, also differentiating for the phenotypes in function and health-related quality of life outcome at 3-month follow-up.

CONCLUSION: The phenotypes may inform the development of targeted interventions aimed at improving the treatment efficiency in patients with common musculoskeletal disorders.

SIGNIFICANCE: This observational prospective study identified five distinct and clinically meaningful phenotypes based on biopsychosocial prognostic factors across common musculoskeletal pain. These phenotypes were independent of primary pain location, showed good external validity, and clear variation in treatment outcome. The findings are particularly valuable as they describe the heterogeneity of patients with musculoskeletal pain and points to a need for more targeted interventions in common musculoskeletal disorders to improve treatment outcome.

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This page is part of the PainScience BIBLIOGRAPHY, which contains plain language summaries of thousands of scientific papers & others sources. It’s like a highly specialized blog. A few highlights:

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